This assignment is for ETC5521 Assignment 1 by Team goanna comprising of XUE WANG, XITONG HE, CUIPING WEI, Chengzhi Ye, Emily Sheehan, and Dea Avega Editya.

1 Introduction and motivation

The Australian climate is generally hot and dry, which means that most regions can be affected by bushfires at anytime of the year (Australia 2020). Bushfires vary in their magnitude and temperature. Some bushfires can go on for days, weeks or even months. Some bushfires are out of control, while others can be contained.

Last year, the bushfires in Victoria and New South Wales captured the attention of people worldwide. They caused destruction and devastation for several months. Around 33 lives were lost, over 1 billion mammals died, and over 3,000 homes were destroyed (Lisa Richards, Nigel Brew, 2020).

This analysis hopes to understand the relationship between climactic conditions and bushfires, and determine whether climate change has influenced the number of bushfires.

R has been used as the main tool for cleaning and analysis. The analysis proceeds as follows; the data description can be found in section 2, the limitations in section 3, the findings in section 4 and the conclusion is in section 5.

1.1 Research questions

The analysis has been divided into three parts; climactic condition, bushfires and the relationship between climatic condition and bushfires.

Climactic condition:

  • Where does rainfall occur most in Australia?
  • What is the hottest climate in Australia?
  • How has global warming impacted temperatures in Australia?

Bushfires:

  • In which months are bushfires burning?
  • Where are the bushfires burning?

Relationship between climactic condition and bushfires:

  • Positive trend for bushfires and temperature
  • Negative trend for bushfires and rain
  • What is the correlation between climactic conditions and bushfires?

2 Data description

This section mainly introduces the data, data sources and data description.
There are three data sets used on this analysis, and the cleaned data is obtained from GitHub tidytuesday.

2.1 Australian Fire Data

The Australian fire data has been extracted from the MODIS fire product collection at NASA (NASA 2020). The fire data is collected every five minutes and there are 5101817 observations from 2000-11-01 to 2020-01-05. All the variables in the dataset have been presented in the table below. The variables predominantly used in this analysis are; latitude, longitude and acquisition date.

Table 2.1: Australia fire data
Variable Description
latitude Center of 1km fire pixel but not necessarily the actual location of the fire as one or more fires can be detected within the 1km pixel.
longitude Center of 1km fire pixel but not necessarily the actual location of the fire as one or more fires can be detected within the 1km pixel.
brightness Channel 21/22 brightness temperature of the fire pixel measured in Kelvin.
scan The algorithm produces 1km fire pixels but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
track The algorithm produces 1km fire pixels but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
acq_date Date of MODIS acquisition.
act_time Time of acquisition/overpass of the satellite (in UTC).
satellite A = Aqua and T = Terra.
confidence This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence estimates range between 0 and 100% and are assigned one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire).
version Version identifies the collection (e.g. MODIS Collection 6) and source of data processing: Near Real-Time (NRT suffix added to collection) or Standard Processing (collection only). ‘6.0NRT’ - Collection 6 NRT processing.’6.0’ - Collection 6 Standard processing. Find out more on collections and on the differences between FIRMS data sourced from LANCE FIRMS and University of Maryland.
dbright_t31 Channel 31 brightness temperature of the fire pixel measured in Kelvin.
frq Depicts the pixel-integrated fire radiative power in MW (megawatts).
day_night D = Daytime, N = Nighttime

2.2 Climate data

The climate data was extracted from the Australian Bureau of Meterology (BoM). The Bureau of Meterology is the weather station that measures rainfall, wind, temperature, etc.

The cleaned Rainfall data was obtained from from GitHub tidytuesday. It has rainfall for six Australian cities, namely; Perth, Adelaide, Melbourne, Sydney, Brisbane and Canberra. It contains more than 230,000 observations and has been collected from 1858-01-01 to 2020-01-06. There was a few missing values for Brisbane and Canberra. To maintain the integrity of the data the missing values have been added from the source website and cleaned so that the data is complete for Canberra (for 1968-01-01 to 2017-12-31) and Brisbane (for 1893-01-01 to 1998-12-31). Therefore, the rainfall dataset used in this analysis is a combination of the two above.

The temperature data has been retrieved from two sources. The first source for temperature data was GitHub tidytuesday, and it has been collected from 1910-01-01 to 2019-05-31. Since the dates for the cleaned temperature data was not consistent with the fire data, a second source was used. The second source for the temperature data was source website. This data was cleaned to obtain temperatures from 2019-06-01 to 2020-01-05. Both datasets were merged to produce the final dataset used for the analysis. The final dataset has around 530,000 observations taken from 1910-01-01 to 2020-01-05. The seven weather stations chosen were based on the seven Australian cities; Perth, Adelaide, Melbourne, Sydney, Brisbane, Port Lincoln and Canberra.

The structure of the climate data is presented in the table below. The year, city name and rainfall variables were mainly used for from the rainfall dataset and the date, temperature and temperature type were predominantly used from the temperature dataset.

Table 2.2: Temperature data
Variable Class Description
city_name character City Name
date double Date
temperature double Temperature in Celsius
temp_type character Temperature type (min/max daily)
site_name character Actual site/weather station
Table 2.3: Rainfall data
Variable Class Description
station_code character Station Code
city_name character City Name
year double year
month character month
day character day
rainfall double Trainfall in millimeters
period double how many days was it collected across
quality character Certified quality or not
lat double latitude
long double longitude
station_name character Station Name

3 Limitations of analysis

The main limitations of the dataset are concerned with the fire and climate data.

There is no regional division in the fire data. Therefore, the data has been assigned to a state or reigion based on its longitude and latitude, which may lead to location bias in the analysis. (borders for NSW an VIc not easily distinguished)

The rainfall and temperature data has been recorded for some major cities, and the sample is relatively small when compared to the fire data. Therefore, the correlation between the fire and climate data in section 4 may not be precisely accurate as the temperature could be for a city which may be hundreds of kilometres away from the fire it has been correlated to. This may cause a deviation in the results.

4 Analysis and findings

4.1 Climate Conditions

4.1.1 Where does rainfall occur the most in Australia?

Figure 4.1: Average monthly rainfall for each state in 2011

Figure 4.1 shows the average monthly rainfall in 2019 for Adelaide, Brisbane, Canberra, Melbourne, Perth and Sydney. The amount of rainfall in each state varies from month to month, which is likely due to each state having slightly different weather patterns and seasons. However, Melbourne, Adelaide and Canberra have similar rainfall patterns in 2011.

4.1.2 Where is the hottest climate in Australia?

Daily Average Temperature for each State Overtime

Figure 4.2: Daily Average Temperature for each State Overtime

Figure 4.2 is a heatmap displaying the daily average temperature for each city. It is clear that the warmest cities are Brisbane and Perth on average. Alarmingly, each area/city is increasing in temperature overtime, which is evidence of global warming. This will be discussed in the next section.

4.1.3 How has climate change impacted weather patterns in Australia?

The plot for the difference between the average temperature of 1961-1990 (as baseline) and the annual average temperature for each year from 1910 to 2019, calculated by daily maximum temperature

Figure 4.3: The plot for the difference between the average temperature of 1961-1990 (as baseline) and the annual average temperature for each year from 1910 to 2019, calculated by daily maximum temperature

Figure 4.3 shows the average temperature difference in Australia from 1910 to 2019. It is compared against the average temperature from 1961-1990. There is a clear upward trend, thus indicating that the average temperature in Australia is increasing. The figure highlights the average temperature for 2019, as it was the highest average temperature on record Meteorology (2019) by over 1.5°C.

Annual rainfall difference 1961-1990 (as baseline) and the annual average rainfall for each year from 1910 to 2019, calculated by daily maximum rainfall

Figure 4.4: Annual rainfall difference 1961-1990 (as baseline) and the annual average rainfall for each year from 1910 to 2019, calculated by daily maximum rainfall

Figure 4.4 shows the average rainfall difference in Australia from 1910 to 2019. The calculated average rainfall for a given year is compared against the average rainfall from 1961-1990. From 1961-1990 the average rainfall is variable, which is likely a result of the natural weather patterns. However, after 1990 there is a clear downward trend, indicating that each year there is less rainfall than the 1961-1990 average.

Moreover, 2019 had one of biggest differences and thus had considerably less rainfall than other years. In 1994, there was a severe drought influenced by the El Niño weather pattern. This was the fifth year of drought for some parts of Australia (Nicholls 2004). In 2010, the annual rainfall was the highest in 20 years which was the result of a La Niña event.

Both figures indicate that climate change has lead to Australia becoming a hotter and drier continent. As mentioned above, this is the ‘perfect storm’ for bushfires.

4.2 Bushfires

4.2.1 When are the fires burning?

Figure 4.5: Yearly Australian fires from 2001 until 2020

Figure 4.5 is a line plot showing the number of bushfires for each year, ordered according to month. The trend line for 2019 is clearly different to other years, which is due to the bushfires in Victoria and New South Wales. These were the biggest bushfires since the European Settlement (Nolan et al. 2020), hence the clear upward trend from September 2019.

In addition, there were more bushfires in September 2011 than in any other year in the same period. According to Blanchi et al. (2014), these bushfires were the result of a combination of low rainfall and strong winds.

The overall trend line shows that bushfires are more likely to occur from August to November. This is the winter-spring period in Australia. These months are typically drier in most parts of Australia as seen in Figure 4.1, which can lead to the ignition of forest fuels (Sullivan et al. 2012) and thus bushfires.

4.2.2 Where are the bushfires burning?

Figure 4.6: The number of bushfire in different states or regions in the past 20 years

Figure 4.6 shows the number of bushfires in the last 20 years according to region. A line has been added to line show the average number of bushfires (over the last 20 years) to make comparison easier. Most bushfires occur in the Northern Territory and Queensland, as seen in Figure 4.6. Both areas are prone to drought and have high concentrations of vegetation. The number of fires in Victoria and New South Wales is relatively stable, with the exception of 2019. As mentioned above, this is due to the catastrophic bushfires that took place over this period.

Figure 4.7 shows the distribution of bushfires from the end of 2019 to the beginning of 2020. It predominantly captures Victoria and NSW, due to the extensive fires in 2019.

Figure 4.7: The distribution point for Australian bushfires from 2019-12-29 to 2020-01-05(the darker the color, the more serious the fire)

4.3 How does temperature and rainfall affect the number of bushfires?

4.3.1 Positive Trend for Bushfires and Temperature

Figure 4.8: The Average Temperature Difference and Average Bushfires during 2000 until 2020

This section is focused on the base assumption that higher temperatures contribute to a higher number of bushfires.

Figure 4.8 shows the association between temperature and bushfires. The temperature variable has been plotted as a temperature difference from the average temperature during a period of observations (2000-2020). Mathematically, the temperature difference is formulated below:

\[ Average\;Temperature\;Difference_n = Annual\;Temperature_n\; - Average\;Temperature\;in\;Period\;of\;Observations\]

Since the average number of bushfires has different scale to temperatures, the annual average bushfires has been scaled down using log 10 and square root. By doing so, the two variables can be placed in a single plot to see the patterns.

Figure 4.8, shows that the annual temperature trend seems to rise from 2000 until 2019, similar to figure 4.3. The average annual number of bushfires has also increased slightly. Therefore, the association seems to be positive, but not strong. As an example, the average number of bushfires rised sharply in 2011 (marked by black dashed line) while the temperature only increased slightly. Additionally, the temperature from 2015 to 2020 has increased dramatically, while the average number of bushfires has only increased slightly.

4.3.2 Negative Trend for Bushfires and Rain

Figure 4.9: Annual Rainfall and Bushfires

This section is based on the assumption that increased rainfall leads to less bushfires.

Figure 4.9 shows the association between rain and bushfires. Similar to above, the temperature variable has been plotted as a temperature difference from the average temperature during 2000-2020. Since the average number of bushfires has different scale to rainfall, the annual average bushfires has been scaled down using log 10. By doing so, the two variables can be placed in a single plot to see the patterns.

Australia’s location means that rainfall is highly variable. It is strongly influenced by the global climate system phenomena such as El Niño, La Niña, and IOD. However, figure 4.9 shows that the annual rainfall is decreasing. Over this time, the average number of bushfires has increased slightly. It is likely there is a weak negative association.

4.3.3 What is the correlation between climactic conditions and bushfires?

This section outlines the correlation between climactic conditions and bushfires.

The correlation between rainfall, temperature and bushfires

Figure 4.10: The correlation between rainfall, temperature and bushfires

Figure 4.10 shows that rainfall and bushfires have a small negative correlation 30%. Therefore, if the average rainfall precipitation increases, the probability of bushfires is likely to decrease by approximately 30%.

As for temperature and bushfires, the correlation between these two variables is only 0.13. Given this correlation is close to 0, there is no correlation between temperature and bushfires in the past 20 years.

The correlation between temperature and precipiation is -0.47, which is the largest absolute value among the three correlations. The correlation coefficient of 0.47 means that if the temperature rises, the precipitation will decrease by 47%. Temperature impacts the rate of evaporation, with higher temperatures leading to drier weather and faster air moisture loss (Hausfather 2018).

5 Conclusions

The analysis has looked into the climactic conditions in Australia. It found that rainfall is quite variable depending on the season, however, Canberra, Adelaide and Melbourne tend to have the lowest amount of rain annually. The warmest climates were Perth and Brisbane. Overtime, annual rainfall is decreasing in each state, and temperature is rising. This is evidence of global warming.

In addition to considering the climactic conditions in Australia, the analysis looked at when, where and what climactic conditions contribute to the most bushfires. It found that bushfires are common from August to November, and are frequently found in the Northern Territory and Western Australia.

A correlation plot was used to conclude the analysis and establish whether climactic condition has an affect on the number of bushfires. It revealed that lack of rainfall is likely to have the most dramatic affect on the number of bushfires. This is consistent with 2019, which was one of the driest years and had the highest number of bushfires. This is concerning as the global warming plot indicates that rainfall is decreasing overtime, meaning more bushfires. More should be done to reverse the affects of global warming, and thus reduce the devastation and destruction caused by bushfires.

Acknowlegments

The authors would like to thank all the contributors to the following R package: Wickham et al. (2019), Wickham (2016), Wickham, Hester, and Francois (2018), Cheng, Karambelkar, and Xie (2019), Ryan and Ulrich (2020), Müller (2017), R Core Team (2020), Arnold (2019), Wickham et al. (2020), Vanderkam et al. (2018), Grolemund and Wickham (2011), Schloerke et al. (2020), Rudis (2020).

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